title: Quantifying condition-dependent intracellular protein levels enables high-precision fitness estimates.
abstract: Countless studies monitor the growth rate of microbial populations as a measure of fitness. However, an enormous gap separates growth-rate differences measurable in the laboratory from those that natural selection can distinguish efficiently. Taking advantage of the recent discovery that transcript and protein levels in budding yeast closely track growth rate, we explore the possibility that growth rate can be more sensitively inferred by monitoring the proteomic response to growth, rather than growth itself. We find a set of proteins whose levels, in aggregate, enable prediction of growth rate to a higher precision than direct measurements. However, we find little overlap between these proteins and those that closely track growth rate in other studies. These results suggest that, in yeast, the pathways that set the pace of cell division can differ depending on the growth-altering stimulus. Still, with proper validation, protein measurements can provide high-precision growth estimates that allow extension of phenotypic growth-based assays closer to the limits of evolutionary selection.
authors.affiliation: Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York, United States of America.
authors.forename: Kerry A
authors.initials: KA
authors.lastname: Geiler-Samerotte
authors.forename: Tatsunori
authors.initials: T
authors.lastname: Hashimoto
authors.forename: Michael F
authors.initials: MF
authors.lastname: Dion
authors.forename: Bogdan A
authors.initials: BA
authors.lastname: Budnik
authors.forename: Edoardo M
authors.initials: EM
authors.lastname: Airoldi
authors.forename: D Allan
authors.initials: DA
authors.lastname: Drummond
mesh_terms: D005656:Fungal Proteins / Q000378:metabolism*; D056084:Genetic Fitness / Q000502:physiology*; D016013:Likelihood Functions; D040901:Proteomics; D004718:Saccharomycetales / Q000254:growth & development* / Q000378:metabolism; D012641:Selection, Genetic; D059467:Transcriptome / Q000235:genetics / Q000502:physiology*
chemical_list: D005656:Fungal Proteins